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Prediction of aflatoxin contamination outbreaks in Texas corn using mechanistic and machine learning models.

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Bibliographic Details
Title: Prediction of aflatoxin contamination outbreaks in Texas corn using mechanistic and machine learning models.
Authors: Castano-Duque L; USDA, Agriculture Research Service, Southern Regional Research Center, New Orleans, LA, United States., Avila A; Department of Mathematics, University of Texas, Arlington, TX, United States., Mack BM; USDA, Agriculture Research Service, Southern Regional Research Center, New Orleans, LA, United States., Winzeler HE; Department of Mathematics, University of Texas, Arlington, TX, United States., Blackstock JM; USDA, Agriculture Research Service, Dale Bumpers Small Farms Research Center, Booneville, AR, United States., Lebar MD; USDA, Agriculture Research Service, Southern Regional Research Center, New Orleans, LA, United States., Moore GG; USDA, Agriculture Research Service, Southern Regional Research Center, New Orleans, LA, United States., Owens PR; USDA, Agriculture Research Service, Dale Bumpers Small Farms Research Center, Booneville, AR, United States., Mehl HL; Center for Advanced Spatial Technologies, University of Arkansas, Fayetteville, AR, United States., Su J; Department of Mathematics, University of Texas, Arlington, TX, United States., Lindsay J; Department of Geosciences, University of Arkansas, Fayetteville, AR, United States., Rajasekaran K; USDA, Agriculture Research Service, Southern Regional Research Center, New Orleans, LA, United States.
Source: Frontiers in microbiology [Front Microbiol] 2025 Mar 05; Vol. 16, pp. 1528997. Date of Electronic Publication: 2025 Mar 05 (Print Publication: 2025).
Publication Type: Journal Article
Journal Info: Publisher: Frontiers Research Foundation Country of Publication: Switzerland NLM ID: 101548977 Publication Model: eCollection Cited Medium: Print ISSN: 1664-302X (Print) Linking ISSN: 1664302X NLM ISO Abbreviation: Front Microbiol Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1664-302X
DOI:10.3389/fmicb.2025.1528997